Snorkel Flow
The data-centric AI platform for automated data labeling, integrated model training and analysis, and enhanced domain expert collaboration. Set a new pace for AI.
The data-centric AI workflow
Training data is the greatest blocker to successfully developing AI applications. Traditional manual labeling is slow, expensive, and hard to iterate, govern, or reuse.
With data-centric AI development, you overcome these challenges. Label data programmatically and continuously improve training data and model quality with guided iteration. Unlock new use cases by capturing knowledge from domain experts, foundation models, and other resources.
The impact of Snorkel Flow
(in 60 seconds)
Your high-value experts have more to offer
Snorkel Flow turns your expertise into a multiplier
And augments your knowledge
So you see faster time-to-value for AI
10-100x faster AI development
Leverage years of research at the Stanford AI lab and the latest AI advancements to rapidly build NLP and other AI applications.
Automate data labeling
Manually labeling data one by one is slow, expensive, and doesn’t scale.
Instead, label programmatically and encode your labeling rationale from diverse knowledge sources. Snorkel Flow intelligently combines, de-noises, and auto-labels training data en-masse.
- Labeling function (LF) builders
Diverse pre-built LFs like pattern- or numeric-based, foundation model prompts, and more. - Active learning
Speed programmatic labeling by prioritizing highest impact slices of data to improve. - Real-time feedback
Get LF and model quality insights as you work with continuous model feedback. - Annotator Suite
Interface for domain experts to label ground truth and troubleshoot during iteration.
Train and analyze models
Better training data is the key to improving model performance. Yet, you can’t improve what you can’t measure.
Snorkel Flow integrates model training, analysis, and guided iteration into a single workflow. Strategically improve training data quality to reach model performance targets fast.
- One-click model training
Choose from a library of leading model architectures, or use the Python SDK to train custom models. - AutoML
Select the best algorithm and hyperparameters for your problem automatically. - Guided iteration
Integrated suite of analysis tools to show you where (and how) to improve both data and models. - Automation
Accelerate further with 1-click automated and auto-suggested actions to improve.
Make optimal use of foundation models
Foundation models (FMs) like BERT, GPT-3, and more can jump-start enterprise AI, but only after expensive fine-tuning on proprietary data.
With Snorkel Flow, users can fine-tune FMs rapidly faster, and distill relevant knowledge from FMs to train higher-quality, lower-cost, more efficient models for production.
- Foundation Model Fine-Tuning
Create large, domain-specific training datasets to adapt FMs for production-grade accuracy. - Foundation Model Warm Start
Use FMs with state-of-the-art zero- and few-shot learning to auto-label training data and train deployable models. - Foundation Model Prompt Builder
Develop, evaluate, and combine prompts to tune the output of FMs to precisely label datasets and train deployable models.
Enterprise proven and ready
Data ingest
Quickly and securely integrate to data pipelines or upload data locally.
Model training
Train custom models or choose from leading model frameworks with optional AutoML.
Production serving
Deploy your models within Snorkel Flow or export to the service of your choice.
Infrastructure
Host Snorkel Flow within the secure infrastructure of your choice.
Let's make it real.
Set a new pace for AI
Schlumberger built an AI app in 3 days
Built an AI application in 3 days that reduced time to extract information from oil well drilling reports from 1 to 3 hours per report to just a few seconds.
Google improved accuracy by 52%
Genentech saved over $10M
Additional platform benefits
Privacy-safe
Governable
Reusable
Collaborative
